The demands of risk and credit analysis today have placed an increasing burden on individuals responsible for reviewing and analyzing relevant documents. The market demands analyses and research that incorporates all known information and reflects a company's current risk and credit profile. These demands are occurring against a backdrop of greater analytic requirements by the market, an accelerating pace of information availability, complexity, and dissemination throughout the markets, and an accelerating growth in the volume and number of SEC filings and other sources of company information. Analysts spend a significant amount of time each year reading SEC filings in addition to their many other tasks and this invention can assist analysts in catching important disclosures as quickly as the market can.
Today's financial market transactions take place in a rapidly expanding universe of unstructured data, as evidenced by, for example, the accelerated growth in the number and volume of SEC filings. Also, there is a risk that some companies may seek to take advantage of the sheer size and complexity of some filings to disguise or play-down potentially adverse developments. Furthermore, source reports such as SEC filings arrive in lumps (e.g. quarterly filing cycles). Thus, there is a need for prioritization for human analysis and a virtually instantaneous, triage-oriented automated analysis of this mass of unstructured information.
U.S. Patent Application Publication 2005/0071217 by Hoogs et al. describes a method, system and computer product for analyzing business risk using event information extracted from natural language sources. Hoogs requires business risk model components which model a business risk measure based on “temporal proximity and temporal order of events by comparing the structured events record to the templates of pattern events stored in the database” or a Bayesian Belief Network in which “the correct prior and conditional probabilities for events and event relationships” must be encoded. Hoogs further requires templates of pattern events comprising “a number and type of events that form a pattern in an event category and temporal constraints that exist between the events” or a case library which contains “types of events, temporal order, and proximity of events, representing each case.” These requirements of Hoogs constrain transfer of analysts' knowledge of risk indicators into the automated system and the type of knowledge that can be represented. Furthermore, information indicative of business risk may not be expressed with temporal language. Additionally, the method and system of Hoogs requires that web-based searches be conducted through a web browser at either “predefined intervals of time or at the prompting of a user of the system.”
Thus, what is needed is a system and method that allows analysts to transfer their knowledge of risk indicators into the automated system without regimented temporal requirements and without needing complex business risk model components. What is needed is a system and method for risk alerting that is not limited to temporal proximities, temporal ordering, and temporal analysis. What is needed is a system and method for evaluating information as it is produced and becomes available. The system and method of the present invention is directed to meet these needs.